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Hi all,
I have an SBML model with an initial assignment from a uniform distribution (model attached).
spt_random.zip
Despite having set the units on the distributions I get a unit validation warning.
It seems like the unit validation does not work with the distributions.
Here the basic structure. An initial assignment from a uniform(0 dimensionless, 1 dimensionless) to a parameter which is dimensionless. I.e. the distribution and the parameter are compatible, but still get the warning below.
<listOfParameters>
<parameter id="protein_random" value="0.5" units="dimensionless" constant="true"/>
</listOfParameters>
<listOfInitialAssignments>
<initialAssignment symbol="protein_random">
<math xmlns="http://www.w3.org/1998/Math/MathML" xmlns:sbml="http://www.sbml.org/sbml/level3/version2/core">
<apply>
<csymbol encoding="text" definitionURL="http://www.sbml.org/sbml/symbols/distrib/uniform"> uniform </csymbol>
<cn sbml:units="dimensionless" type="integer"> 0 </cn>
<cn sbml:units="dimensionless" type="integer"> 1 </cn>
</apply>
</math>
</initialAssignment>
</listOfInitialAssignments>WARNING E0: SBML unit consistency (core, L91, code) validation.py:186
[Warning] Missing unit declarations on parameters or literal numbers in expression
In situations where a mathematical expression contains literal numbers or parameters whose units have not been declared, it is not possible to verify accurately the consistency of the units in the
expression.
The units of the <initialAssignment> <math> expression 'uniform(0, 1)' cannot be fully checked. Unit consistency reported as either no errors or further unit errors related to this object may not
be accurate. Probably similar things happen with the other csymbol distributions.
Best Matthias
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